Beth has been recording her son's weight each year for the past 10 years, as shown in the table below:

To evaluate the statements regarding the relationship between the recorded age and weight based on the data Beth has collected, you would typically need to perform a few steps. Since I don't have the actual data from the table you mentioned, I can guide you on how to analyze the scatter plot and make conclusions as per the statements given.

1. Create a scatter plot in Desmos:

   • Input the recorded data points (age, weight) into Desmos to create a scatter plot.
   • Each point represents a year with the corresponding weight of her son.

2. Assess the line of best fit:

   • Once you have the scatter plot, add the line given in the statement (y = 5x + 15).
   • Observe how well the line fits the data points. If the line closely approaches most of the data points, this suggests that the statement about the line of best fit could be True. If not, it is False.

3. Determine correlation:

   • Look at the scatter plot to see if there’s any visible trend. If the points trend upwards (or downwards) as age increases, there is likely a correlation. If the points are scattered randomly, then there may be no correlation.

4. Evaluate linear association:

   • If there is a clear trend in the scatter plot where the points are somewhat aligned in a straight pattern (even if it’s not perfect), you can suggest a linear association exists. If it appears random or non-linear, then the association is likely not linear.

Evaluating the Statements

After following these steps, here’s how you would assess the statements:

1. “The data can be represented with a line of best fit y=5x+15”:

   • If the line closely fits the data: True. If it does not: False.

2. “There is no correlation between the recorded age and weight.”:

   • If you see any upward or downward trend: False. If the data points are random: True.

3. “The data suggests a linear association between the recorded age and weight.”:

   • If points trend in a straight line pattern: True. If points are scattered randomly without a pattern: False.

Conclusion

By conducting this analysis as described, you will be able to evaluate the accuracy of each of the statements regarding the relationship between age and weight as recorded by Beth. Make sure to refer to the scatter plot for the most accurate conclusions.